The google-dialogflow2 library allows access to all features of the Google Dialogflow service.

This documentation was generated from Dialogflow crate version 6.0.0+20240614, where 20240614 is the exact revision of the dialogflow:v2 schema built by the mako code generator v6.0.0.

Everything else about the Dialogflow v2 API can be found at the official documentation site.

Features

Handle the following Resources with ease from the central hub ...

• projects

• agent entity types batch delete, agent entity types batch update, agent entity types create, agent entity types delete, agent entity types entities batch create, agent entity types entities batch delete, agent entity types entities batch update, agent entity types get, agent entity types list, agent entity types patch, agent environments create, agent environments delete, agent environments get, agent environments get history, agent environments intents list, agent environments list, agent environments patch, agent environments users sessions contexts create, agent environments users sessions contexts delete, agent environments users sessions contexts get, agent environments users sessions contexts list, agent environments users sessions contexts patch, agent environments users sessions delete contexts, agent environments users sessions detect intent, agent environments users sessions entity types create, agent environments users sessions entity types delete, agent environments users sessions entity types get, agent environments users sessions entity types list, agent environments users sessions entity types patch, agent export, agent get fulfillment, agent get validation result, agent import, agent intents batch delete, agent intents batch update, agent intents create, agent intents delete, agent intents get, agent intents list, agent intents patch, agent knowledge bases create, agent knowledge bases delete, agent knowledge bases documents create, agent knowledge bases documents delete, agent knowledge bases documents get, agent knowledge bases documents list, agent knowledge bases documents patch, agent knowledge bases documents reload, agent knowledge bases get, agent knowledge bases list, agent knowledge bases patch, agent restore, agent search, agent sessions contexts create, agent sessions contexts delete, agent sessions contexts get, agent sessions contexts list, agent sessions contexts patch, agent sessions delete contexts, agent sessions detect intent, agent sessions entity types create, agent sessions entity types delete, agent sessions entity types get, agent sessions entity types list, agent sessions entity types patch, agent train, agent update fulfillment, agent versions create, agent versions delete, agent versions get, agent versions list, agent versions patch, answer records list, answer records patch, conversation datasets get, conversation datasets import conversation data, conversation datasets list, conversation models create, conversation models delete, conversation models deploy, conversation models evaluations get, conversation models evaluations list, conversation models get, conversation models list, conversation models undeploy, conversation profiles clear suggestion feature config, conversation profiles create, conversation profiles delete, conversation profiles get, conversation profiles list, conversation profiles patch, conversation profiles set suggestion feature config, conversations complete, conversations create, conversations get, conversations list, conversations messages list, conversations participants analyze content, conversations participants create, conversations participants get, conversations participants list, conversations participants patch, conversations participants suggestions suggest articles, conversations participants suggestions suggest faq answers, conversations participants suggestions suggest knowledge assist, conversations participants suggestions suggest smart replies, conversations suggestions search knowledge, conversations suggestions suggest conversation summary, delete agent, generators create, generators list, get agent, knowledge bases create, knowledge bases delete, knowledge bases documents create, knowledge bases documents delete, knowledge bases documents export, knowledge bases documents get, knowledge bases documents import, knowledge bases documents list, knowledge bases documents patch, knowledge bases documents reload, knowledge bases get, knowledge bases list, knowledge bases patch, locations agent entity types batch delete, locations agent entity types batch update, locations agent entity types create, locations agent entity types delete, locations agent entity types entities batch create, locations agent entity types entities batch delete, locations agent entity types entities batch update, locations agent entity types get, locations agent entity types list, locations agent entity types patch, locations agent environments create, locations agent environments delete, locations agent environments get, locations agent environments get history, locations agent environments intents list, locations agent environments list, locations agent environments patch, locations agent environments users sessions contexts create, locations agent environments users sessions contexts delete, locations agent environments users sessions contexts get, locations agent environments users sessions contexts list, locations agent environments users sessions contexts patch, locations agent environments users sessions delete contexts, locations agent environments users sessions detect intent, locations agent environments users sessions entity types create, locations agent environments users sessions entity types delete, locations agent environments users sessions entity types get, locations agent environments users sessions entity types list, locations agent environments users sessions entity types patch, locations agent export, locations agent get fulfillment, locations agent get validation result, locations agent import, locations agent intents batch delete, locations agent intents batch update, locations agent intents create, locations agent intents delete, locations agent intents get, locations agent intents list, locations agent intents patch, locations agent restore, locations agent search, locations agent sessions contexts create, locations agent sessions contexts delete, locations agent sessions contexts get, locations agent sessions contexts list, locations agent sessions contexts patch, locations agent sessions delete contexts, locations agent sessions detect intent, locations agent sessions entity types create, locations agent sessions entity types delete, locations agent sessions entity types get, locations agent sessions entity types list, locations agent sessions entity types patch, locations agent train, locations agent update fulfillment, locations agent versions create, locations agent versions delete, locations agent versions get, locations agent versions list, locations agent versions patch, locations answer records list, locations answer records patch, locations conversation datasets create, locations conversation datasets delete, locations conversation datasets get, locations conversation datasets import conversation data, locations conversation datasets list, locations conversation models create, locations conversation models delete, locations conversation models deploy, locations conversation models evaluations create, locations conversation models evaluations get, locations conversation models evaluations list, locations conversation models get, locations conversation models list, locations conversation models undeploy, locations conversation profiles clear suggestion feature config, locations conversation profiles create, locations conversation profiles delete, locations conversation profiles get, locations conversation profiles list, locations conversation profiles patch, locations conversation profiles set suggestion feature config, locations conversations complete, locations conversations create, locations conversations get, locations conversations list, locations conversations messages list, locations conversations participants analyze content, locations conversations participants create, locations conversations participants get, locations conversations participants list, locations conversations participants patch, locations conversations participants suggestions suggest articles, locations conversations participants suggestions suggest faq answers, locations conversations participants suggestions suggest knowledge assist, locations conversations participants suggestions suggest smart replies, locations conversations suggestions search knowledge, locations conversations suggestions suggest conversation summary, locations delete agent, locations generators create, locations generators delete, locations generators get, locations generators list, locations generators patch, locations get, locations get agent, locations knowledge bases create, locations knowledge bases delete, locations knowledge bases documents create, locations knowledge bases documents delete, locations knowledge bases documents export, locations knowledge bases documents get, locations knowledge bases documents import, locations knowledge bases documents list, locations knowledge bases documents patch, locations knowledge bases documents reload, locations knowledge bases get, locations knowledge bases list, locations knowledge bases patch, locations list, locations operations cancel, locations operations get, locations operations list, locations set agent, locations stateless suggestion generate, locations suggestions generate stateless summary, locations suggestions search knowledge, operations cancel, operations get, operations list, set agent, suggestions generate stateless summary and suggestions search knowledge

Structure of this Library

The API is structured into the following primary items:

• Hub
  • a central object to maintain state and allow accessing all Activities
  • creates Method Builders which in turn allow access to individual Call Builders
• Resources
  • primary types that you can apply Activities to
  • a collection of properties and Parts
  • Parts
    • a collection of properties
    • never directly used in Activities
• Activities
  • operations to apply to Resources

All structures are marked with applicable traits to further categorize them and ease browsing.

Generally speaking, you can invoke Activities like this:

let r = hub.resource().activity(...).doit().await

Or specifically ...

let r = hub.projects().agent_entity_types_entities_batch_create(...).doit().await
let r = hub.projects().agent_entity_types_entities_batch_delete(...).doit().await
let r = hub.projects().agent_entity_types_entities_batch_update(...).doit().await
let r = hub.projects().agent_entity_types_batch_delete(...).doit().await
let r = hub.projects().agent_entity_types_batch_update(...).doit().await
let r = hub.projects().agent_intents_batch_delete(...).doit().await
let r = hub.projects().agent_intents_batch_update(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_create(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_delete(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_patch(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_reload(...).doit().await
let r = hub.projects().agent_export(...).doit().await
let r = hub.projects().agent_import(...).doit().await
let r = hub.projects().agent_restore(...).doit().await
let r = hub.projects().agent_train(...).doit().await
let r = hub.projects().conversation_datasets_import_conversation_data(...).doit().await
let r = hub.projects().conversation_models_create(...).doit().await
let r = hub.projects().conversation_models_delete(...).doit().await
let r = hub.projects().conversation_models_deploy(...).doit().await
let r = hub.projects().conversation_models_undeploy(...).doit().await
let r = hub.projects().conversation_profiles_clear_suggestion_feature_config(...).doit().await
let r = hub.projects().conversation_profiles_set_suggestion_feature_config(...).doit().await
let r = hub.projects().knowledge_bases_documents_create(...).doit().await
let r = hub.projects().knowledge_bases_documents_delete(...).doit().await
let r = hub.projects().knowledge_bases_documents_export(...).doit().await
let r = hub.projects().knowledge_bases_documents_import(...).doit().await
let r = hub.projects().knowledge_bases_documents_patch(...).doit().await
let r = hub.projects().knowledge_bases_documents_reload(...).doit().await
let r = hub.projects().locations_agent_entity_types_entities_batch_create(...).doit().await
let r = hub.projects().locations_agent_entity_types_entities_batch_delete(...).doit().await
let r = hub.projects().locations_agent_entity_types_entities_batch_update(...).doit().await
let r = hub.projects().locations_agent_entity_types_batch_delete(...).doit().await
let r = hub.projects().locations_agent_entity_types_batch_update(...).doit().await
let r = hub.projects().locations_agent_intents_batch_delete(...).doit().await
let r = hub.projects().locations_agent_intents_batch_update(...).doit().await
let r = hub.projects().locations_agent_export(...).doit().await
let r = hub.projects().locations_agent_import(...).doit().await
let r = hub.projects().locations_agent_restore(...).doit().await
let r = hub.projects().locations_agent_train(...).doit().await
let r = hub.projects().locations_conversation_datasets_create(...).doit().await
let r = hub.projects().locations_conversation_datasets_delete(...).doit().await
let r = hub.projects().locations_conversation_datasets_import_conversation_data(...).doit().await
let r = hub.projects().locations_conversation_models_evaluations_create(...).doit().await
let r = hub.projects().locations_conversation_models_create(...).doit().await
let r = hub.projects().locations_conversation_models_delete(...).doit().await
let r = hub.projects().locations_conversation_models_deploy(...).doit().await
let r = hub.projects().locations_conversation_models_undeploy(...).doit().await
let r = hub.projects().locations_conversation_profiles_clear_suggestion_feature_config(...).doit().await
let r = hub.projects().locations_conversation_profiles_set_suggestion_feature_config(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_create(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_delete(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_export(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_import(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_patch(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_reload(...).doit().await
let r = hub.projects().locations_operations_get(...).doit().await
let r = hub.projects().operations_get(...).doit().await

The resource() and activity(...) calls create builders. The second one dealing with Activities supports various methods to configure the impending operation (not shown here). It is made such that all required arguments have to be specified right away (i.e. (...)), whereas all optional ones can be build up as desired. The doit() method performs the actual communication with the server and returns the respective result.

Usage

Setting up your Project

To use this library, you would put the following lines into your Cargo.toml file:

[dependencies]
google-dialogflow2 = "*"
serde = "1"
serde_json = "1"

A complete example

extern crate hyper;
extern crate hyper_rustls;
extern crate google_dialogflow2 as dialogflow2;
use dialogflow2::api::GoogleCloudDialogflowV2Document;
use dialogflow2::{Result, Error};
use dialogflow2::{Dialogflow, FieldMask, hyper_rustls, hyper_util, yup_oauth2};

// Get an ApplicationSecret instance by some means. It contains the `client_id` and
// `client_secret`, among other things.
let secret: yup_oauth2::ApplicationSecret = Default::default();
// Instantiate the authenticator. It will choose a suitable authentication flow for you,
// unless you replace  `None` with the desired Flow.
// Provide your own `AuthenticatorDelegate` to adjust the way it operates and get feedback about
// what's going on. You probably want to bring in your own `TokenStorage` to persist tokens and
// retrieve them from storage.
let auth = yup_oauth2::InstalledFlowAuthenticator::builder(
    secret,
    yup_oauth2::InstalledFlowReturnMethod::HTTPRedirect,
).build().await.unwrap();

let client = hyper_util::client::legacy::Client::builder(
    hyper_util::rt::TokioExecutor::new()
)
.build(
    hyper_rustls::HttpsConnectorBuilder::new()
        .with_native_roots()
        .unwrap()
        .https_or_http()
        .enable_http1()
        .build()
);
let mut hub = Dialogflow::new(client, auth);
// As the method needs a request, you would usually fill it with the desired information
// into the respective structure. Some of the parts shown here might not be applicable !
// Values shown here are possibly random and not representative !
let mut req = GoogleCloudDialogflowV2Document::default();

// You can configure optional parameters by calling the respective setters at will, and
// execute the final call using `doit()`.
// Values shown here are possibly random and not representative !
let result = hub.projects().agent_knowledge_bases_documents_patch(req, "name")
             .update_mask(FieldMask::new::<&str>(&[]))
             .doit().await;

match result {
    Err(e) => match e {
        // The Error enum provides details about what exactly happened.
        // You can also just use its `Debug`, `Display` or `Error` traits
         Error::HttpError(_)
        |Error::Io(_)
        |Error::MissingAPIKey
        |Error::MissingToken(_)
        |Error::Cancelled
        |Error::UploadSizeLimitExceeded(_, _)
        |Error::Failure(_)
        |Error::BadRequest(_)
        |Error::FieldClash(_)
        |Error::JsonDecodeError(_, _) => println!("{}", e),
    },
    Ok(res) => println!("Success: {:?}", res),
}

Handling Errors

All errors produced by the system are provided either as Result enumeration as return value of the doit() methods, or handed as possibly intermediate results to either the Hub Delegate, or the Authenticator Delegate.

When delegates handle errors or intermediate values, they may have a chance to instruct the system to retry. This makes the system potentially resilient to all kinds of errors.

Uploads and Downloads

If a method supports downloads, the response body, which is part of the Result, should be read by you to obtain the media. If such a method also supports a Response Result, it will return that by default. You can see it as meta-data for the actual media. To trigger a media download, you will have to set up the builder by making this call: .param("alt", "media").

Methods supporting uploads can do so using up to 2 different protocols: simple and resumable. The distinctiveness of each is represented by customized doit(...) methods, which are then named upload(...) and upload_resumable(...) respectively.

Customization and Callbacks

You may alter the way an doit() method is called by providing a delegate to the Method Builder before making the final doit() call. Respective methods will be called to provide progress information, as well as determine whether the system should retry on failure.

The delegate trait is default-implemented, allowing you to customize it with minimal effort.

Optional Parts in Server-Requests

All structures provided by this library are made to be encodable and decodable via json. Optionals are used to indicate that partial requests are responses are valid. Most optionals are are considered Parts which are identifiable by name, which will be sent to the server to indicate either the set parts of the request or the desired parts in the response.

Builder Arguments

Using method builders, you are able to prepare an action call by repeatedly calling it's methods. These will always take a single argument, for which the following statements are true.

• PODs are handed by copy
• strings are passed as &str
• request values are moved

Arguments will always be copied or cloned into the builder, to make them independent of their original life times.

Cargo Features

• utoipa - Add support for utoipa and derive utoipa::ToSchema on all the types. You'll have to import and register the required types in #[openapi(schemas(...))], otherwise the generated openapi spec would be invalid.

License

The dialogflow2 library was generated by Sebastian Thiel, and is placed under the MIT license. You can read the full text at the repository's license file.